Impact of surgeon variability on outcomes after total shoulder arthroplasty: an analysis of 2188 surgeons

Background

There has been limited evaluation of surgeon-specific factors on outcomes after total shoulder arthroplasty (TSA). The goals of this study were (1) to determine the impact of surgeon procedural volume, career duration, practice type, and fellowship training on TSA outcomes at 2-year follow-up and (2) to evaluate the relative importance of surgeon variables in relation to patient variables in influencing outcomes.

Methods

The PearlDiver Mariner database was queried to identify all surgeons who performed a minimum of 11 TSA procedures from 2010 to 2018. An Internet search of publicly available data was performed to determine the career duration, practice type, and fellowship training of each surgeon. Multivariate logistic regression models were built to determine the relationship between surgeon-specific variables and 2-year surgical complications and revisions and 90-day readmissions. Variable importance of patient-specific and surgeon-specific factors was determined by the Akaike information criterion increase of these models.

Results

A total of 2188 surgeons who performed 93,122 TSA procedures were identified in this database. Higher reverse TSA surgical volume was associated with fewer surgical complications and revisions, although such a relationship was not observed for anatomic TSA. Revision after anatomic TSA was more common among surgeons who were in their first 5 years of practice. There was a higher risk of surgical complication and readmission among academic surgeons, but this did not equate with a higher risk of revision. The impact of these surgeon-specific factors on outcomes was small in relation to patient-level variables, such as age, sex, and number of medical comorbidities.

Conclusion

Surgeon procedural volume, career duration, and practice setting influence the surgical complication, revision, and readmission rates after TSA. The impact of surgeon factors was small relative to patient variables, highlighting the importance of patient selection in mitigating adverse outcomes.